The redundancy in digital image representation can be classified into two categories: local and global. In this paper, we present an analysis of two image characteristics that give rise to local and global redundancy in image representation. Based on this study, we propose a lossless image compression scheme that exploits redundancy both at local and global levels in order to obtain maximum compression efficiency. The proposed algorithm segments the image into variable size blocks and encodes them depending on the characteristics exhibited by the pixels within the block. The proposed algorithm is implemented in software and its performance is better than other lossless compression schemes such as the Huffman, the arithmetic, the Lempel-Ziv and the JPEG.
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